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#

decision-tree-algorithm

Here are 83 public repositories matching this topic...

I've demonstrated the working of the decision tree-based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample. All the steps have been explained in detail with graphics for better understanding.

  • UpdatedDec 9, 2022
  • Jupyter Notebook

C++ code for "A Faster Drop-in Implementation for Leaf-wise Exact Greedy Induction of Decision Tree Using Pre-sorted Deque"

  • UpdatedMay 2, 2023
  • C++

MasterThesis on Congestion Detection in SDN networks using Machine Learning

  • UpdatedNov 19, 2017
  • Python

Implementation of Grid Search to find better hyper-parameters for decision tree to reduce the over fitting.

  • UpdatedMay 29, 2021
  • Jupyter Notebook

The code uses the scikit-learn machine learning library to train a decision tree on a small dataset of body metrics (height, width, and shoe size) labeled male or female. Then we can predict the gender of someone given a novel set of body metrics.

  • UpdatedSep 30, 2017
  • Python

Implementation of Decision Tree Algorithm using Python, Pandas, and NumPy without using any off the shelf library usi

  • UpdatedJan 27, 2023
  • Jupyter Notebook

QUEST is proposed by Loh and Shih (1997), and stands for Quick, Unbiased, Efficient, Statistical Tree. It is a tree-structured classification algorithm that yields a binary decision tree. A comparison study of QUEST and other algorithms was conducted by Lim et al (2000).

  • UpdatedJan 30, 2018
  • C++

决策树代码简单实现

  • UpdatedDec 13, 2022
  • C++

Prediction using Decision Tree Algorithm to create Decision Tree Classifier.

  • UpdatedJan 28, 2021
  • Jupyter Notebook

Distributed Decision Tree Induction using MPI

  • UpdatedSep 15, 2017
  • C++

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